Many physiological processes require cells to adaptively regulate their morphological and motile properties in response to local environmental factors and conditions. Cells gain such control by employing numerous cytoskeletal regulatory proteins (CRPs) that function collectively to generate, maintain and remodel different forms of actin and microtubule cytoskeletal structures. The overexpression of several CRPs in many forms of cancer been associated with poor prognosis. Yet, the impact of these perturbations on cytoskeletal regulation and oncogenic cell behaviors is largely unknown. While focusing on a class of CRPs believed to function as master cytoskeletal regulators (IQGAPs, WAVEs), this project will develop a new multi-scale approach to dissect composite states of CRP networks and establish functional relationships relating them to morphodynamic cell behaviors. Our approach integrates tools from the fields of synthetic biology, DNA nanotechnology, super-resolution microscopy, and systems biology in order to: (i) modulate the states of individual and multiple CRPs in cells; (ii) characterize their nanometer-scale localization patterns; and (iii) determine how CRP network states and composite morphological cell phenotypes respond mechanistically to perturbations. Expression-based perturbations will be introduced using novel gene expression technologies that provide precise and uniform control over mammalian protein expression in a cell population while introducing minimal disruptions to cell physiology. Such control will open new opportunities to screen phenotypic responses to specific CRP perturbations in high-throughput imaging assays while we adjust the expression levels and spatial distributions of single and multiple CRPs (Aim 1). Spatially-delineated, network- level analyses of CRP distributions will be enabled by a new, single-molecule 'barcoding' super resolution imaging procedure that offers opportunities to characterize the localization patterns of several dozens of CRPs (and potentially many more) simultaneously within the same cell, while also allowing ultra-structural features of actin and microtubule networks to be resolved (Aim 2). These new technologies will be linked through computational image analyses and state machine modeling of cell responses in order to identify distinct cell phenotypes and predict their responses to CRP perturbations (Aim 3). The synergistic collaborative effort of three investigators with complementary expertise will improve the understanding of CRP network function, thereby promoting the development of new disease treatments.